Provide an example of a stratified sampling method.

• A. Sample from a single region.
• B. Divide population into strata by region, then sample from each stratum proportionally or equally.
• C. Sample every member of the population.
• D. Sample by convenience.

Answer: (B)

Stratified sampling works by first dividing the population into strata that are similar within each group but different between groups. Then you sample from each stratum, either in proportion to its size or with equal numbers from each stratum.

For example, imagine surveying teachers across a country and you want to make sure regional differences are captured. You would split the teacher population into regional groups (North, South, East, West). From each region you then select a sample—perhaps the same number of teachers from each region, or a number proportional to how many teachers exist in that region. Combining these per-stratum samples gives an overall sample that represents all regions and typically reduces sampling error compared to sampling from just one region or using a non-systematic approach.

Why other methods don’t fit: sampling from a single region ignores regional variation; surveying everyone would be a census, not a sample; and sampling by convenience selects whatever is easiest, which orients the sample toward the easiest-to-reach individuals rather than ensuring representation across the population.